This paper describes our experiments on the two tasks of the TREC 2007 Enterprise track. In data preprocessing stage we stripped the non-letter character from documents and query. For the Document Search, we built the index by indri and lemur, handled the query topic and then retrieved relevant documents by indri and lemur. For the Expert Search, we recognized candidates from collection, established correlative document pool, built the index by indri and lemur, and then got expert list and supporting documents.